NeuroMotor PenTM Report

Published

March 9, 2023

Parkinson’s Disease Evaluation

Important

This report is intended to assist qualified Health Care Profesionals (HCP) in the assessment of an individual referred under the suspicion of having Parkinson’s Disease.

Clinical Context

This report presents several AI metrics derived from objective measures from individuals performing a battery of test using Manus Neurodynamica NeuroMotor PenTM.

These presented metrics combine factors from detailed measurement recordings made whilst the individual performs a battery of well established neurological test tasks.

The metrics have been assessed in a UK reference population and an individual’s results are presented in this clinical context. The HCP should review Clinical,Reference, Study et al [1] to establish applicability and limitations.

The information in this report should be used in the context of a full neurological assessment conducted to the current standard of care practices to establish a diagnosis.

Subject and Recording Details

Subject ID test
Sex MALE
Dominant hand LEFT
Test date and time 2023-02-09 22:01
Test battery Circle, Spiral, Elel, FITTS Short Modified, FITTS Long Modified, ZigZag, ZigZag Offset
Operator comment

Overall Assessment

Subject performance similar to PD population (recommend review of report details)

Clinical context

In the clinical reference population, 29 individuals with a value less than 0.62 were subsequently diagnosed with PD. That is, 69.05% of the PD diagnoses in the study.

Additionally, 0 individuals with a value greater or equal to 0.62 were subsequently diagnosed as not having PD. That is, 0.0% of the non PD diagnoses in the study.

Note

We need to look into this whole ‘confidence’ thing. It is really confusing. In the above plot I have shown 1.0 - reported conf for the ‘predicted as non PD individuals’. I am not happy with the obvious 0.5 clipping above. We would expect this in a classifier operating on it’s own training data and not a real world clinical test.

Symptom Scores

These mini boxplots show the scores in a clinical context. Currently against the ‘Walker study’ data. A bigger pool would be much better (so max 83 individuals, usually lower if raw data did not result in successful classification).

Micrographia Features

The micrographia symptom assessment is derived from a combination of factors in the elel task.

{'FN': 19, 'TN': 14, 'TP': 23, 'FP': 16}

Tremor Features

{'FN': 39, 'TN': 27, 'TP': 3, 'FP': 3}

Bradykinesia

{'FN': 2, 'TN': 2, 'TP': 40, 'FP': 28}

Spatial Accuracy

{'FN': 5, 'TN': 3, 'TP': 37, 'FP': 27}

Test Battery Details

2023-03-09 16:39:34.078 | INFO     | neuromotor_pen.data:_parse_header:693 - Loading New Data Version...
ManusData_pd_test_09022023100926.JSON

Circle

Circle Segment 1

Duration 3.8 s, Accuracy Estimate 2.006 (lower is better)

Circle Segment 2

Duration 2.76 s, Accuracy Estimate 2.777 (lower is better)

Circle Segment 3

Duration 2.76 s, Accuracy Estimate 2.528 (lower is better)

Circle Segment 4

Duration 2.76 s, Accuracy Estimate 2.202 (lower is better)

Circle Segment 5

Duration 2.36 s, Accuracy Estimate 2.819 (lower is better)

Circle Segment 6

Duration 2.44 s, Accuracy Estimate 2.874 (lower is better)

Circle Segment 7

Duration 2.12 s, Accuracy Estimate 4.665 (lower is better)

Circle Segment 8

Duration 2.4 s, Accuracy Estimate 2.43 (lower is better)

Circle Segment 9

Duration 2.36 s, Accuracy Estimate 2.818 (lower is better)

Circle Segment 10

Duration 2.16 s, Accuracy Estimate 4.653 (lower is better)

Spiral

Spiral Segment 1

Duration 9.68 s, Accuracy Estimate 2.316 (lower is better)

Spiral Segment 2

Duration 8.96 s, Accuracy Estimate 2.175 (lower is better)

Spiral Segment 3

Duration 9.12 s, Accuracy Estimate 2.266 (lower is better)

Spiral Segment 4

Duration 9.44 s, Accuracy Estimate 2.291 (lower is better)

Spiral Segment 5

Duration 9.4 s, Accuracy Estimate 1.949 (lower is better)

Spiral Segment 6

Duration 8.16 s, Accuracy Estimate 2.168 (lower is better)

Spiral Segment 7

Duration 7.52 s, Accuracy Estimate 2.307 (lower is better)

Spiral Segment 8

Duration 8.48 s, Accuracy Estimate 2.202 (lower is better)

Spiral Segment 9

Duration 8.2 s, Accuracy Estimate 2.059 (lower is better)

Spiral Segment 10

Duration 12.2 s, Accuracy Estimate 1.597 (lower is better)

Elel

Elel Segment 1

Elel Segment 2

Elel Segment 3

Elel Segment 4

Elel Segment 5

Elel Segment 6

Elel Segment 7

Elel Segment 8

Elel Segment 9

Elel Segment 10

FITTS Short Modified

FITTS Long Modified

ZigZag

ZigZag Segment 1

Duration 6.56 s, Accuracy Estimate 4.375 (lower is better)

ZigZag Segment 2

Duration 5.6 s, Accuracy Estimate 4.553 (lower is better)

ZigZag Segment 3

Duration 5.6 s, Accuracy Estimate 4.149 (lower is better)

ZigZag Segment 4

Duration 5.8 s, Accuracy Estimate 3.603 (lower is better)

ZigZag Segment 5

Duration 5.52 s, Accuracy Estimate 4.406 (lower is better)

ZigZag Offset

ZigZag Offset Segment 1

Duration 5.32 s, Accuracy Estimate 0.059 (lower is better)

ZigZag Offset Segment 2

Duration 4.8 s, Accuracy Estimate 0.048 (lower is better)

ZigZag Offset Segment 3

Duration 4.84 s, Accuracy Estimate 0.05 (lower is better)

ZigZag Offset Segment 4

Duration 5.0 s, Accuracy Estimate 0.05 (lower is better)

ZigZag Offset Segment 5

Duration 4.28 s, Accuracy Estimate 0.096 (lower is better)

Appendices

Misc

Currently a dumping ground for things that could be included or previous output style.

Note

Putting all the results out here but will not be in a final report.

HiSpec {‘HiSpec_class’: ‘NOT PD’, ‘HiSpec_score’: 0.63}
RanFor {‘RanFor_class’: ‘PD’, ‘RanFor_score’: 0.62}
BM_May22 {‘BM_May22_class’: ‘PD’, ‘BM_May22_score’: 0.6581378343237094}
BM_HC_Sep22 {‘BM_HC_Sep22_class’: ‘Patient’, ‘BM_HC_Sep22_score’: 0.7032407530939824}
BM_PD_Sep22 {‘BM_PD_Sep22_class’: ‘PD’, ‘BM_PD_Sep22_score’: 0.7137867214078727}